1. Field of the Invention
The present invention relates to an information processing apparatus, an information processing method, and a computer-readable storage medium.
2. Description of the Related Art
In a field of an image forming device, known has been a technique of comparing operation sound data obtained by collecting sounds by a sound collector with operation sound data prepared in advance for each of operation statuses based on context information to detect an abnormity.
Specifically, Japanese Laid-open Patent Publication No. 2006-184722 discloses an image forming device including a function of comparing operation sound data, collected and stored in advance, of units (a drum motor, a paper feeding motor, a fixing motor, a developing clutch, and the like) with operation sound data collected by operating the image forming device, making a detection as an abnormal sound when a difference therebetween is equal to or more than a predetermined level, and specifying a unit causing the abnormal sound by using an operation sequence table of each of the units, for example.
Besides, Japanese Laid-open Patent Publication No. 2012-177748 discloses an image forming device including a function of making a comparison with data, collected and stored in advance, of abnormal sounds caused in each part when an operation sound, collected by operating the image forming device, of each part increases and determining an abnormity when the operation sound corresponds to the abnormal sound data.
However, those techniques of detecting an abnormity by using context information and operation sound data require operation sound data for each of operation statuses, which leads to a problem of causing a relative reduction in an amount of operation sound data available for each of the operation statuses, a deterioration in an approximation accuracy of a model expressing operation sounds, and a deterioration in a detection accuracy as a result.
This problem will be explained with reference to Tables 1 and 2 below. Here, Table 1 illustrates an example of context information and Table 2 illustrates examples of operation statuses by taking the context information into account.
TABLE 1No.Context informationOperation flag1Driving motor of fixingON/OFFunit2Conveyance motorON/OFF3Speed-up zone of paperPaper present/Papernot present4Manual conveyance motorON/OFF5Ozone fanON/OFF6Number of rotations ofLow/Highozone fan7Light emission of LEDON/OFF8Remaining amount ofSmall/Largetoner9Manual conveyance rollerON/OFF
TABLE 2ContextOperationOperationOperationNo.informationstatus 1status 2status 3. . .1Driving motorONOFFOFF. . .of fixing unit2ConveyanceONONOFF. . .motor3Speed-up zonePaper notPaper notPaper. . .of paperpresentpresentpresent4ManualONOFFON. . .conveyancemotor5Ozone fanONONOFF. . .6Number ofLowHigh—. . .rotations ofozone fan7Light emissionONONOFF. . .of LED8RemainingSmallSmallLarge. . .amount oftoner9ManualOFFOFFON. . .conveyanceroller
In Table 1, an operation flag of each of items for the context information is defined by 0/1 (two conditions by division with a threshold in a case of an analog quantity). In using the context information of all the items in Table 1, the number of possible operation statuses is 29 (=512) (however, the actual number of possible operation statuses becomes smaller to some extent since there exist some impossible operation statuses). Examples of operation statuses on this occasion are illustrated in Table 2. While only three kinds of examples are illustrated here, there are, in fact, 512 kinds of assumable operation statues in total.
In assuming a collection of an actual operation sound data, the data amount of collectable operation sounds has a limit in practice due to a capacity of a storage medium, difficulty in reproducing operation statuses, and the like. Especially, for collecting abnormal operation sound data, a human person is required to keep collecting sounds by operating the device and to judge and extract abnormal sounds that have occurred incidentally, and is not able to generate at will and freely collect such abnormal sounds.
On the assumption that the data amount of collectable operation sounds is constant since the data amount is limited in practice as explained, the reason why an approximation accuracy of a model is deteriorated will be explained. A model is configured to be expressed by mean and variation. Generally speaking, in using and expressing by mean and variation a certain data group, a larger amount of data enables more accurate expression of the data group by the mean and the variation. However, in a case where the data amount is insufficient, it is difficult to see a distribution state of the entirety of the data, which causes deterioration in validity of the mean and the variation. This situation is described as “approximation accuracy is low”. Therefore, an insufficient data amount causes a low approximation accuracy of the model.
On the assumption that context information includes nine items illustrated in FIG. 1 and there is data of 512 sounds, the number of operation statuses becomes 29 (=512) since the number of pieces of context information directly affects the number of operation statuses. Therefore, the number of sounds as data to be allotted to one operation status is “one in the mean”. The reason of using the expression “mean” is that there is non-existent operation status and there are multiple operation statuses in the data of 512 sounds.
As explained above, there is a problem that the number of pieces of data to be allotted to one operation status is small, the approximation accuracy of a model expressing operation sounds is deteriorated, and the accuracy of the detection of abnormal sounds becomes low in the conventional techniques of performing a clustering on (dividing) operation statuses for the number of pieces of context information.
Therefore, there is a need for an information processing apparatus, an information processing method, and a computer-readable storage medium, capable of enhancing the approximation accuracy of model expressing operation sounds of a device such as an image forming device and improving the accuracy of the detection of abnormal sounds.